[Simulation of PM_2.5 Concentration Based on Optimized Indexes of 2D/3D Urban Form]

It is well known that urban forms can affect the source distribution and diffusion process of air pollution; however, practical quantitative methods and models on alleviating urban air pollution by optimizing urban form indexes are lacking. Using Chang Sha city as an example, we quantitatively analyzed the PM_2.5 concentration distribution in terms of 2D/3D urban form indexes (e.g., land use functionality, landscape pattern, and development intensity). Based on this, the urban form regulation-aided air quality optimization model (UFR-AQOM) was proposed and consequently employed to simulate the scene-dependent PM_2.5 concentrations under double constraints from both the index threshold and air quality objectives. The results showed that the high value area of PM_2.5 concentration in Chang Sha featured a "one axis and four nodes" spatial pattern. PM_2.5 concentrations in grids with commercial or road land applications, high patch density or high Shannon index, and high land plot ratio or low sky openness were shown to be relatively higher. The development intensity indexes had the greatest impact on the spatial variation in PM_2.5 concentration, followed by landscape pattern and land use functionality, and the interaction of factor indexes could significantly strengthen their own single contributions. The UFR-AQOM model, taking into account the contribution differences and interactions among different factors, could effectively simulate the spatial variation in PM_2.5 concentration in urban areas (R²=0.65,RMSE=1.40 μg·m^-3). In order to meet the regulations of PM_2.5 standards, the overall management of landscape pattern indexes, such as the integral dimension of the perimeter surface and patch density, should be strengthened in the main urban area of Changsha. Further, the zoned optimization of PM_2.5 concentrations could be implemented by controlling the urban land use indexes, such as the industrial land use ratio and water area ratio, as well as the development intensity indexes such as the land use area ratio. These research results provided support for decisions in the optimization of national territory spatial planning indexes targeting air quality improvement.